Başlık için İstatistik Bölümü Koleksiyonu listeleme
Toplam kayıt 95, listelenen: 48-67
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Large-scale global optimization based on hybrid swarm intelligence algorithm
(IOS Press, 2020)There are numerous large-scale global optimization problems encountered in real-world applications including engineering, manufacturing, economics, networking fields. Over the last two decades different varieties of swarm ... -
Mapping the forest fire risk zones using artificial intelligence with risk factors data
(SPRINGER HEIDELBERG, 2022)Geographical information system data has been used in forest fire risk zone mapping studies commonly. However, forest fires are caused by many factors, which cannot be explained only by geographical and meteorological ... -
Modeling of Tunnel Boring Machine Performance Employing Random Forest Algorithm
(Springer Science and Business Media Deutschland GmbH, 2023)Prediction of tunnel boring machine (TBM) performance is still a challenging research subject in engineering geology, geotechnical engineering, and tunnel engineering communities. The longest railway tunnel with approximately ... -
Modelling Right-Censored Data with Partially Linear Model and Feed Forward Neural Networks: A Methodological Study
(Türkiye klinikleri, 2022)Objective: Modeling right-censored data becomes a challenging task in survival analysis, due to having an incomplete data structure. When the response variable is rightcensored, classical estimation methods cannot be used ... -
Modified estimators in semiparametric regression models with right-censored data
(Taylor & Francis Ltd, 2018)In this work we introduce different modified estimators for the vector parameter and an unknown regression function g in semiparametric regression models when censored response observations are replaced with synthetic data ... -
Modified Local Linear Estimators in Partially Linear Additive Models with Right-Censored Data Based on Different Censorship Solution Techniques
(MDPI, 2023)This paper introduces a modified local linear estimator (LLR) for partially linear additive models (PLAM) when the response variable is subject to random right-censoring. In the case of modeling right-censored data, PLAM ... -
Modified spline regression based on randomly right-censored data: A comparative study
(Taylor & Francis Inc, 2018)In this paper, we propose modified spline estimators for nonparametric regression models with right-censored data, especially when the censored response observations are converted to synthetic data. Efficient implementation ... -
Monitoring exponentially distributed time between events data: self-starting perspective
(TAYLOR & FRANCIS INC, 2021)Time between events (TBE) control charts have been widely used to monitor high yield processes. Traditionally, an estimated in-control occurrence rate from a Phase I dataset is used to calculate the control limits when the ... -
MSstatsQC 2.0: R/Bioconductor Package for Statistical Quality Control of Mass Spectrometry-Based Proteomics Experiments
(Amer Chemical Soc, 2019)MSstatsQC is an R/Bioconductor package for statistical monitoring of longitudinal system suitability and quality control in mass spectrometry-based proteomics. MSstatsQC was initially designed for targeted selected reaction ... -
MSstatsQC: Longitudinal System Suitability Monitoring and Quality Control for Targeted Proteomic Experiments
(Amer Soc Biochemistry Molecular Biology Inc, 2017)Selected Reaction Monitoring (SRM) is a powerful tool for targeted detection and quantification of peptides in complex matrices. An important objective of SRM is to obtain peptide quantifications that are (1) suitable for ... -
A New Estimation Method Based on Order Statistics in the Families of Symmetric Location-scale Distributions
(Taylor & Francis Inc, 2016)In this study, new unbiased and nonlinear estimators based on order statistics are proposed for the family of symmetric location-scale distributions and these estimators can be computed from both uncensored and symmetric ... -
New estimators based on order statistics in some families of scale distributions
(Taylor & Francis Inc, 2017)In this study some new unbiased estimators based on order statistics are proposed for the scale parameter in some family of scale distributions. These new estimators are suitable for the cases of complete (uncensored) and ... -
A New Fuzzy Time Series Model Based on Fuzzy C-Regression Model
(Springer, 2018)This study proposes a new fuzzy time series model based on Fuzzy C-Regression Model clustering algorithm (FCRMF). There are two major superiorities of FCRMF in comparison with existing fuzzy time series model based on fuzzy ... -
A new fuzzy time series model based on robust clustering for forecasting of air pollution
(Elsevier Science Bv, 2018)In this study, a new Fuzzy Time Series (FTS) model based on the Fuzzy K-Medoid (FKM) clustering algorithm is proposed in order to forecast air pollution. FTS models generally have some advantages when compared with other ... -
A new robust ridge parameter estimator based on search method for linear regression model
(Taylor & Francis Ltd, 2020)A large and wide variety of ridge parameter estimators proposed for linear regression models exist in the literature. Actually proposing new ridge parameter estimator lately proving its efficiency on few cases seems endless. ... -
A new statistical early outbreak detection method for biosurveillance and performance comparisons
(Wiley, 2019)Biosurveillance for rapid detection of epidemics of diseases is a challenging area of endeavor in many respects. Hence, this area is in need of development of methodology and opens to novel methods of detection. In this ... -
Nonparametric regression estimates based on imputation techniques for right-censored data
(Springer Verlag, 2020)Censored data is a kind of data type where the exact value of a response variable is not completely known. Therefore, this case is a problem that should be solved in order to obtain an accurate and efficient data analysis. ... -
ON THE ADAPTIVE NADARAYA-WATSON KERNEL REGRESSION ESTIMATORS
(Hacettepe Univ, Fac Sci, 2010)Nonparametric kernel estimators are widely used in many research areas of statistics. An important nonparametric kernel estimator of a regression function is the Nadaraya-Watson kernel regression estimator which is often ... -
ON THE PERFORMANCE OF THE SEMIPARAMETRIC BINARY RESPONSE MODEL WHEN THE TRUE MODEL IS PARAMETRIC LOGISTIC
(Hacettepe Univ, Fac Sci, 2010)In this article, a simulation study is performed to reveal the deviations of the semiparametric binary response model from its parametric counterpart, based on various scenarios including different sample sizes, different ... -
Optimum shrinkage parameter selection for ridge type estimator of Tobit model
(Taylor and Francis Ltd., 2020)This paper presents different ridge type estimators based on maximum likelihood ((Formula presented.)) for parameters of a Tobit model. In this context, an algorithm is introduced to get the estimators based on (Formula ...
